A number of organizations are continuously collecting large quantities of data which can then be analyzed. The analysis may involve real-time analytics and/or may involve analysis of historical data. The data which is being collected may evolve over time.
Consider the example where the data relates to one or more games of a company. Analysis may be in relation to a single game or to data collected over a number of different games. Additionally there may be more than one platform provided, with different games. New games may be added to the portfolio of games. A decision may be taken that some new data needs to be collected.
Some computer implemented games may have a very large number of players, each having associated data such as identity (user-name), email, scores, time played, and other associated data which may be provided by the user, for example social network accounts and associated friends therein.
Game analytics is used to analyse data associated with games. The game analytic data can be used for a number of different purposes such as to understand user behaviour, enhance games, anomaly detection or the like. Managing the very large quantity of data for data analytics is challenging.